Method and system for detecting internal short circuit (ISC) in a battery and battery cell implementing such ISC detection method

Abstract

A method for detecting an internal short circuit (ISC) in an electrochemical cell based on online measurement and processing of thermodynamic data and kinetic data about the electrochemical cell. The thermodynamic data includes open circuit voltage (OCV) data, entropy (ΔS) data and / or enthalpy (ΔH) data and combinations thereof. The kinetic data includes the voltage of the battery, the temperature of the battery, the internal resistance and current of the battery and combinations thereof.

Description

[0001] This patent application claims priority to Singapore Patent Application No. 10201804493S filed on May 28, 2018. Technical Field

[0002] The present invention relates to a method for detecting an internal short circuit (ISC) in a battery. The present invention also relates to a system and a battery cell for implementing the detection method. Background Art

[0003] A battery cell consists of an anode (negative electrode), a cathode (positive electrode), an electrolyte, and a separator. During normal operation, such as discharging a primary battery (disposable) and charging and discharging a secondary (rechargeable) battery, ions and electrons flow simultaneously. Ions flow inside the cell between the anode and cathode due to the electrolyte, while electrons flow out of the cell into a load (such as a mobile phone) during discharge and into a charger during charging.

[0004] There should be no flow of electrons between the anode and cathode inside the battery. For this reason, a separator is used between the anode and cathode to avoid any physical contact between the anode and cathode. If electrons flow inside the cell, this leads to self-discharge of the cell and loss of capacity, which is undesirable.

[0005] An internal short circuit (ISC) occurs in a battery cell when the anode and cathode are in direct electrical contact with each other inside the cell.

[0006] Since there is a voltage difference ΔV (in volts (V)) between the anode and cathode, the electrical contact between the anode and cathode will generate a current I (in amperes (A)), commonly referred to as the ISC current or internal leakage current.

[0007] The ISC has an ohmic resistance R (in ohms (Ω)) between the anode and the cathode.

[0008] The current flow between the anode and cathode is given by Ohm's law: ΔV=RI (1).

[0009] In equation (1), ΔV and R vary with time, and the ISC current I also varies with time.

[0010] When current I flows into resistor R, heat power is generated according to Joule's law: P(W) = RI 2 (2).

[0011] Because of the internal heat generated by the ISC, the local temperature may rise, eventually triggering a thermal event in the cell, such as thermal runaway.

[0012] Therefore, ISC raises safety issues in battery cells.

[0013] ISC is considered one of the main causes of battery thermal events such as thermal runaway, gassing, fire, and explosion.

[0014] The main reasons for ISC in battery cells are:

[0015] 1) Metal dendrite growth on the anode surface, which eventually crosses the separator, causing a short circuit. Dendrite growth has been reported for anodes based on Li and Zn chemistries.

[0016] 2) Particles of metal and other conductive materials in the battery cell due to manufacturing defects, electrode disintegration and dissolution / precipitation processes,

[0017] 3) rupture of the separator between the anode and cathode due to fatigue and / or mechanical stress within the cell, and

[0018] 4) Defective battery cell design.

[0019] If one cell in a battery pack experiences thermal runaway, the generated heat propagates to neighboring cells, which in turn experience thermal runaway, leading to a catastrophic chain of thermal events. For example, during thermal runaway in a lithium-ion battery, the temperature of the cell may rise to over 1000°C, resulting in metal melting and hot metal particle emissions. Because ISCs pose a serious safety risk, it is important to develop methods and systems that can detect the early stages of ISC formation before a thermal event occurs in a battery cell. Summary of the invention

[0020] The present invention provides a method and system for detecting ISC in a battery cell, and involves using thermodynamic and kinetic data to detect ISC in a battery cell. The method is applicable to any type of battery, including but not limited to lithium ion battery cells (LIB), nickel cadmium cells (NiCd), nickel metal hydride cells (NIMH), lead acid batteries (LAB), zinc air cells, zinc manganese dioxide cells, redox flow batteries, lithium manganese oxide cells, lithium sulfur cells and lithium air cells.

[0021] Useful thermodynamic data in the present invention include, but are not limited to, open circuit voltage (OCV), entropy (ΔS) data, and enthalpy (ΔH) data, and combinations thereof.

[0022] Useful kinetic data include, but are not limited to, the voltage of the battery cell, the temperature of the battery cell, the internal resistance and current of the battery cell, and combinations thereof.

[0023] Since the integrated circuit includes intelligent chips for managing single cells and multiple cells (cell modules, cell groups), thermodynamic and kinetic data can be measured and processed online.

[0024] Using equations (3) and (4), ΔS and ΔH are determined from OCV and the temperature dependence of OCV:

[0025]

[0026]

[0027] Where E0 is the OCV, x = state of charge, T = temperature, p = pressure, and F = Faraday constant.

[0028] Plot the OCV data, ΔS data and ΔH data against the charge capacity and discharge capacity (Ah) of the cell and / or against the state of charge (SOC) of the cell and / or the state of discharge (SOD, SOD=100-SOC) of the cell. ΔS data and ΔH data are also usually plotted against the OCV of the cell. The OCV, ΔS and ΔH curves change as the battery ages, which is related to the state of health (SOH) of the cell.

[0029] The voltage of the battery cell changes with the SOC. The voltage of the battery cell increases during charging and decreases during discharging.

[0030] When the cell is at rest after charging or discharging (no external current flows in the cell), the OCV versus time curve of the cell changes with SOC, SOH and temperature "T":

[0031] OCV(t)=f(SOC,SOH,T) (5)

[0032] This process is called voltage relaxation of the battery cell.

[0033] At fixed SOC and T, the OCV tends to stabilize towards the equilibrium OCV over time.

[0034] The variation of OCV with T enables the measurement of ΔS and ΔH at a well-defined SOC and measured OCV, as shown in equations (3) and (4).

[0035] Significant differences have been found in the thermodynamic and kinetic data between cells with and without ISC. Differences were found in the following aspects:

[0036] OCV, ΔS and ΔH vs. SOC curves

[0037] ΔS and ΔH vs. OCV curve

[0038] OCV relaxation curves at different SOC and temperature

[0039] Cell voltage versus capacity curve during charge and discharge

[0040] Comparative analysis of thermodynamic and kinetic data enabled early stage detection of ISC.

[0041] At a fixed cell's OCV, the ΔS data and ΔH data are significantly different when the cell has ISC compared to when the cell does not have ISC.

[0042] At a defined SOC / SOD of the cell, the OCV relaxation curves of the cell with ISC and the cell without ISC after charging or discharging are different.

[0043] The measured differences in the thermodynamic and kinetic data between cells with and without ISC are larger than the error bars, enabling the detection of ISC.

[0044] We have developed a method and system based on the collection and analysis of thermodynamic and kinetic data to detect ISC in battery cells.

[0045] Thermodynamic and kinetic data can be recorded and processed online thanks to smart chips attached to single cells and multiple cells.

[0046] Smart chips consist of integrated circuits with processors and communication capabilities (such as infrared communication).

[0047] The smart chip is part of a system designed to detect ISC in battery cells.

[0048] • The method and system for ISC detection in the present invention is applicable to any type of electrochemical cell chemistry, such as primary cells (non-rechargeable) and secondary cells (rechargeable).

[0049] It is clearly shown that the thermodynamic data curves for each state of charge and OCV are different when the cell has an internal short circuit (ISC) (Example 1000, Example 100, Example 10, and Example 1) than when the cell has no ISC (Example ∞).

[0050] The difference between the thermodynamic data in a cell with or without ISC depends on SOC, SOH (aged cell) and temperature.

[0051] • For well-defined cell chemistries and SOH, there are specific OCVs where differences in thermodynamic and / or kinetic data are more important.

[0052] One method of detecting ISC includes bringing the cell to a specific one of the specific OCVs and measuring the OCV versus T relaxation curve about the specific OCV.

[0053] The second method of detecting ISC involves bringing the cell to one of the specific SOC / SODs and measuring the OCV vs. T relaxation curve for the specific SOC / SOD.

[0054] • Analysis of voltage relaxation curves at a specific OCV and a specific SOC / SOD provides an accurate tool to detect ISC.

[0055] The entropy and enthalpy data for SOC / SOD as well as for OCV are sensitive to the presence of ISC, compared to the baseline data when there is no ISC in the cell.

[0056] • The new method disclosed herein is applicable to all types of battery chemistries.

[0057] The OCV relaxation curves of cells with and without ISC at the same SOC are simulated using the empirical formula:

[0058]

[0059] Three fitting parameters are calculated: U0, A1 and t1.

[0060] The parameters are different for cells with and without ISC, especially the t1 parameter. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] These and other features and advantages of the present invention will be better understood with regard to the following detailed description, appended claims and accompanying drawings, in which:

[0062] Figure 1 is a functional scheme of the ISC detection system and method according to the present invention,

[0063] Figure 2 The OCV versus capacity is shown in the example.

[0064] Figure 3 It is OCV to SOC,

[0065] Figure 4 is the enthalpy to OCV,

[0066] Figure 5 is the entropy to OCV,

[0067] Figure 6 is the enthalpy of SOD,

[0068] Figure 7 is the entropy to SOD,

[0069] Figure 8 is the OCV at @0% SOC (charging) versus time and temperature, example ∞

[0070] Fig. 9 is the OCV at @0% SOC (charge) versus time and temperature, Example 10

[0071] Fig.10 is the OCV at @0% SOC (charge) vs. time, temperature, Example 100

[0072] Fig.11 is the OCV vs. time @ 60% SOC with a fitting curve

[0073] Fig.12 is the OCV vs. time @70% SOC with a fitted curve

[0074] Fig.13 is the OCV vs. time @80% SOC with a fitting curve

[0075] Fig.14 is a table with OCV vs. time fitting parameters U0, A1 and t1,

[0076] Figures 15 to 32 The experimental 2D and 3D graphs of SOD and SOH using 6 cells are shown.

[0077] Fig.33 yes Figures 15 to 32 A summary table of the experiments,

[0078] Figures 34 to 38 The differential entropy versus OCV of 5 cells with ISC is shown.

[0079] Fig.39 The specific OCVs at which the entropy is such that the 6 cells with ISC (CH1 to CH6) and the reference cell (average entropy without ISC) differ substantially are shown.

[0080] Fig.40 The specific SOC at which the entropy is substantially different for the 6 cells (CH1 to CH6) with ISC and the reference battery (average entropy without ISC) is shown,

[0081] Fig.41 is the enthalpy versus SOC curve of the 6 cells (CH1 to CH6) with ISC and the reference cell (average entropy without ISC),

[0082] Fig.42 is the enthalpy versus OCV curves of the 6 cells (CH1 to CH6) with ISC and the reference cell (average entropy without ISC),

[0083] Fig.43 is the entropy versus SOC curve of the 6 cells (CH1 to CH6) with ISC and the reference cell (average entropy without ISC),

[0084] Fig.44 is the entropy versus OCV curve of 6 cells (CH1 to CH6) with ISC and the reference cell (average entropy without ISC),

[0085] Fig.45 is the OCV vs. SOC curve of 6 cells (CH1 to CH6) with ISC and the reference cell (average entropy without ISC),

[0086] Two series of tests were performed on Li-ion batteries (Cell A and Cell B) with a rated capacity of approximately 600 mAh from two different sources and chemistries. Figures 2 to 10 The test results for cell A are shown, and Figure 11 to Figure 45 This is the test result for cell B. DETAILED DESCRIPTION

[0087] refer to Figure 1 The ISC detection system 10 is implemented to detect a possible internal short circuit in an electrochemical cell 1, which is, for example, a LIB cell rated at 600 mAh. The detection system 10 comprises: a unit 2 for measuring (i) the change in open circuit voltage OCV and temperature T as a function of time in order to obtain thermodynamic data and (ii) kinetic data about the electrochemical cell; a data processing unit 3, which receives the thermodynamic data and kinetic data and processes the thermodynamic data and kinetic data by comparing them with reference data or basic data 4 related to the nominal electrochemical cell; a wireless communication unit 5, which is configured to transmit the ISC detection data to a remote control system.

[0088] To simulate ISC, cells A and B are loaded with external resistors (R Ex ) (as shown in the schematic diagram).

[0089] For cell A:

[0090] -1kΩ (Example 1)

[0091] -10kΩ (Example 10)

[0092] -1000kΩ (Instance 100)

[0093] -1000kΩ (instance 1000)

[0094] -∞kΩ (infinite instances, no ISC)

[0095] A cell without a resistor (instances unlimited) was tested as the base cell.

[0096] Using four identical cells with and without external resistor R ExEach test was performed under the same conditions to check the data reproducibility.

[0097] For cell B:

[0098] - CH1 and CH2 are 1000kΩ cells 1 and 2 respectively,

[0099] - CH3 and CH4 are 100kΩ cells 3 and 4 respectively,

[0100] - CH5 and CH6 are 10kΩ cells 5 and 6 respectively,

[0101] (CHn = test channel "n" of the BA 3000 machine, 1≤n≤6)

[0102] Before attaching (or not attaching) an external resistor to the cell, the cell was fully charged or fully discharged at ambient temperature (about 25° C.) using an Arbin battery cycler (at C / 6 rate, here 100 mA).

[0103] Once the cell is fully charged or fully discharged, a resistor is attached to the cell and the cell is transferred to the BA 3000 machine for immediate thermodynamic and kinetic data measurements following the following protocol:

[0104] The fully charged cells were discharged from 100% SOC to 0% SOC in 5% steps. In each step, a discharge current of 100 mA was applied for 18 minutes, followed by rest. Discharging continued until the cell voltage reached the 2.5 V cutoff voltage.

[0105] The fully discharged cells were charged from 0% SOC to 100% SOC in 5% steps. In each step, a charging current of 100mA was applied for 18 minutes followed by rest. Charging continued until the cell voltage reached the 4.2V cutoff voltage.

[0106] After each charging and discharging step, the OCV was monitored at ambient temperature until the OCV stabilized (voltage relaxation typically took about 30 minutes).

[0107] The temperature was then decreased in 5°C steps from ambient temperature 25°C to 20°C, 15°C and 10°C and then back to ambient temperature. At each temperature, the OCV was measured until the OCV stabilized (where voltage relaxation typically took about 20 minutes).

[0108] The OCV vs. T data enables the measurement of entropy and enthalpy according to equations (3) and (4).

[0109] Experiments on thermodynamic data

[0110] Thermodynamic data includes plots of discharge capacity, SOC / SOD for OCV, and OCV, entropy, and enthalpy data for SOC and OCV for entropy and enthalpy, including (entropy, enthalpy, SOC) 3D plots. This is for cell A at Figures 2 to 7 As shown in the example, and for the battery cell B Figure 15 to Figure 45 Example in.

[0111] OCV curve

[0112] For cell A Figure 2 The OCV of the capacity and Figure 3 OCV to SOC, and for cell B Fig.45 The OCV vs. SOC shows the difference in OCV curves between cells with simulated ISC (Examples 1, 10, 100, 1000 for Cell A and Cells 1 to 6 (CH1 to CH6) for Cell B) and cells without ISC (Example ∞ for Cell A and "Average" for Cell B). The difference in OCV curves can be used to detect ISC, albeit less extended than the entropy and enthalpy curves, as will be illustrated in the next section.

[0113] Enthalpy (ΔH) curve

[0114] Enthalpy versus OCV curve Figure 4 In the example of cell A, Fig.42 The enthalpy versus SOC curve is shown in Figure 2. Figure 6 In the example of cell A, Fig.41 exemplified for cell B in FIG. The difference in enthalpy curves for both OCV and SOC between cells with simulated ISC and cells without ISC is significantly greater than the OCV curve presented above. Therefore, enthalpy curve analysis is useful for ISC detection.

[0115] Due to the different chemistries and / or constructions of Cell A and Cell B, the enthalpy curves of Cell A and Cell B for both OCV and SOC are significantly different.

[0116] Entropy (ΔS) curve

[0117] Entropy vs. OCV curve Figure 5 In the example of cell A, Fig.44 The entropy on the SOC curve is shown in Figure 2. Figure 7 In the example of cell A, Fig.43 exemplified for cell B. The differences in the entropy curves for both OCV and SOC between cells with simulated ISC and cells without ISC are significantly greater than the OCV curves presented above. Therefore, entropy curve analysis is useful for ISC detection.

[0118] Here again, due to the different chemistries and / or constructions of cells A and B, the entropy curves for both OCV and SOC of cells A and B are significantly different.

[0119] Entropy (ΔS), enthalpy (ΔH), SOC curve

[0120] Fig.15 , Fig.18 , Fig.21 , Fig.24 , Fig. 27 and Fig.30 The entropy (ΔS), enthalpy (ΔH), and SOC 3D full curves of cells B#1 to #6 with and without ISC are shown, respectively.

[0121] Fig.17 , Fig. 20 , Fig.23 , Fig.26 , Fig.29 and Fig.32 3D zoom curves of entropy (ΔS), enthalpy (ΔH), SOC of cells B#1 to #6 with and without ISC are shown, respectively. The zoom curves highlight the difference between cells with and without ISC.

[0122] Fig.16 , Fig.19 , Fig. 22 , Fig.25 , Fig.28 and Fig.31 The 2D projections of the entropy (ΔS), enthalpy (ΔH), and SOC curves of cells B#1 to #6 with and without ISC on the (entropy, enthalpy) plane are shown. These entropy versus enthalpy 2D representations better highlight the differences between cells with simulated ISC and without ISC. Fig.16 , Fig.19 , Fig. 22 , Fig.25 , Fig.28 and Fig.31 The enthalpy domains where the entropy data are significantly different between cells with and without ISC are clearly circled in the figure. These specific enthalpy domains can be used for ISC detection. These specific enthalpy domains correspond to specific OCV domains and SOC domains of the cells, such as for cell A in Figure 5 and Figure 6 As shown in Fig.41 and Fig.42 as shown in . Fig.39 The OCV domain averages show a large difference between cells with ISC and without ISC, with the OCV domain averages for cell B being 3.7V, 3.8V, 3.92V, and 3.96V. Fig.40The SOC domain average values ​​are shown to be relatively different between cells with ISC and cells without ISC, which are 55%, 60%, 80%, and 90%.

[0123] It should be emphasized here that the specific OCV and SOC values ​​that are useful for online detection of ISC are: 1) average values ​​within the OCV and SOC domains; and 2) cell chemistry and state of health (SOH) dependent.

[0124] Therefore, for a particular cell chemistry and a cell SOH, a method for ISC detection may include driving the cell voltage to an average OCV value among the average OCV values ​​of cell B (such as 3.7V, 3.8V, 3.92V, and 3.96V), and measuring entropy data and enthalpy data around the specific OCV value. If the difference in entropy is higher than the error bar, then the cell is likely to have ISC. Similarly, another method for ISC detection includes driving the cell to a specific SOC and measuring the entropy and enthalpy at the SOC. If the difference in entropy is higher than the error bar, then the cell is likely to have ISC.

[0125] exist Figures 34 to 38 An illustration of the application of an ISC detection method and system is illustrated in FIG, which shows differential entropy data versus OCV between a cell with and without ISC. The differential entropy at each OCV is given by the following formula:

[0126] Δ(ΔS(OCV))=|ΔS ISC (OCV)-ΔS no-ISC (OCV)| (8),

[0127] Among them, || is the absolute value symbol, ΔS ISC (OCV) is the entropy of the cell with ISC at OCV, and ΔS no-ISC (OCV) is the entropy of the cell without ISC at the same OCV.

[0128] Figures 34 to 38 The maximum values ​​at specific OCV values ​​are shown. These specific OCV values ​​can be used to detect ISC in the cells online by entropy measurement and comparison with standard cells without ISC.

[0129] SOC vs. entropy (ΔS) and enthalpy (ΔH)

[0130] In patent application #PCT / IB2018 / 059751, a method and system for online determination of the SOC of primary and rechargeable batteries using the following empirical formula is disclosed:

[0131] SOC=α+βΔS+γΔH (7),

[0132] Among them, the α, β, and γ coefficients are specific to the battery chemistry and SOH.

[0133] Here, the SOC of battery B with and without ISC is fitted by equation (7). Fig.17 , Fig. 20 , Fig.23 , Fig.26 , Fig.29 and Fig.32 The α, β, and γ coefficients for the SOC optimization simulation of cells B#1 to #6 are shown respectively.

[0134] Table 1 below summarizes the achieved fitting data and the coefficient of determination R 2 . It can be seen that the α, β, and γ coefficients are different depending on the presence or absence of ISC. Therefore, the SOC fit using Equation 7 can be used as a method and system for detecting ISC in a battery cell. The α, β, and γ coefficients can be used alone or in combination to detect ISC by comparing with a standard cell without ISC.

[0135]

[0136] Kinetic test data

[0137] Figure 8 , Fig. 9 and Fig.10 The time dependence of OCV on temperature for cell A of Example ∞, Example 10, and Example 100 at the same SOC of 10% is illustrated, respectively. These data are used for entropy and enthalpy determination according to Equation 3 and Equation 4, respectively. It can be easily seen that the OCV versus time curves at various temperatures are different regardless of whether the cell has ISC (Example 10 and Example 100) or does not have ISC (Example ∞). In addition, as shown in Table 2 below, the OCV after time relaxation at various SOCs is different between cells with ISC and cells without ISC. Therefore, the OCV versus time curve and the temperature curve are useful for detecting ISC compared to cells without ICS. Similarly, after time relaxation, the OCV at a well-defined SOC also indicates the presence of ISC.

[0138]

[0139]

[0140]

[0141] Another embodiment of the present invention is the data analysis and simulation of isothermal voltage relaxation curves after discharge at specific SOC and OCV of cells with and without ISC. Fig.11 , Fig.12 and Fig.13 The OCV curves of cell B with ISC at SOC of 60%, 70% and 80% are shown, as well as the same curves for cell B without ISC. The OCV curves during relaxation are in good agreement with the empirical formula:

[0142]

[0143] Where U(t) = time "t" dependent OCV, U0 = equilibrium OCV (t = ∞), A1 = pre-exponential coefficient, and t1 = constant.

[0144] Of course, the present invention is not limited to the above detailed embodiments, and many other versions of the ISC detection method and system according to the present invention can be implemented without departing from the scope of the present invention.

Claims

1. A detection method for detecting an internal short circuit ISC in an electrochemical cell from online measurement and processing of thermodynamic and kinetic data about the electrochemical cell, The thermodynamic data include open circuit voltage OCV data, entropy ΔS data as a function of the open circuit voltage OCV and / or enthalpy ΔH data as a function of the open circuit voltage OCV, and combinations thereof, The kinetic data includes the voltage of the electrochemical cell, the temperature of the electrochemical cell, the internal resistance and current of the electrochemical cell, and combinations thereof, The thermodynamic data and the kinetic data processing comprises comparing the measured thermodynamic data and the kinetic data with reference data related to the electrochemical cell, the reference data being thermodynamic data and kinetic data of an electrochemical cell without an internal short circuit ISC, It is characterized in that The method further comprises the steps of measuring a relaxation curve of the open circuit voltage (OCV) with different states of charge (SOC) and temperatures of the electrochemical cell and comparing the measured relaxation curve with a reference curve, wherein the reference curve is an OCV relaxation curve of an electrochemical cell without an internal short circuit (ISC) after charging or discharging.

2. The detection method according to claim 1, characterized in that: The detection method is implemented in an integrated circuit configured to manage a single battery cell or a plurality of battery cells.

3. The detection method according to claim 1 further comprises a step of measuring entropy ΔS and / or enthalpy ΔH as a function of open circuit voltage OCV, and a step of comparing the entropy and / or enthalpy with a reference change value, wherein the reference change value is an average entropy and / or average enthalpy of an electrochemical cell without an internal short circuit ISC.

4. The detection method according to claim 1, further comprising the following steps: The electrochemical cell is caused to reach a specific open circuit voltage OCV corresponding to a significant difference in thermodynamic data and / or kinetic data, A relaxation curve of the open circuit voltage OCV as a function of temperature (T) is measured with respect to the specific OCV.

5. The detection method according to claim 1, further comprising the following steps: Entropy data and / or enthalpy data are measured as a function of the state of charge SOC or state of discharge SOD and as a function of the open circuit voltage OCV.

6. The detection method according to claim 1, wherein the detection method is applied to a battery cell, and the detection method further comprises the following steps: A set of coefficients α, β, γ specific to the chemistry and state of health SOH of the battery cell is determined and fitted so that the state of charge SOC of the battery cell can be determined as a function of entropy ΔS and enthalpy ΔH according to the following equation: SOC=α+βΔS+γΔH The set of coefficients α, β, γ are compared with reference coefficients corresponding to a reference battery cell without an internal short circuit.

7. The detection method according to claim 1, further comprising the step of sending internal short circuit (ISC) detection data to a remote processing system.

8. A detection system for detecting an internal short circuit (ISC) in an electrochemical cell, the detection system comprising a device for online measurement of thermodynamic data and kinetic data, and a device for processing the thermodynamic data and kinetic data about the electrochemical cell, The means for measuring the thermodynamic data include means for measuring open circuit voltage OCV data, entropy ΔS data as a function of the open circuit voltage OCV and / or enthalpy ΔH data as a function of the open circuit voltage OCV, and combinations thereof, The device for measuring the kinetic data includes a device for measuring the cell voltage, the cell temperature, the cell internal resistance and the current, and a combination thereof, The device for processing thermodynamic and kinetic data comprises a device for comparing the measured thermodynamic and kinetic data with reference data related to the electrochemical cell, the reference data being thermodynamic and kinetic data of an electrochemical cell without an internal short circuit ISC, It is characterized in that The detection system also includes a device for measuring the relaxation curve of the open circuit voltage OCV as the electrochemical cell changes with different charge states SOC and temperature, and a device for comparing the measured relaxation curve with a reference curve, wherein the reference curve is the OCV relaxation curve of the electrochemical cell without an internal short circuit ISC after charging or discharging.

9. The detection system according to claim 8, characterized in that: The detection system includes an integrated circuit configured to manage a single battery cell or a plurality of battery cells.

10. The detection system according to claim 8 further comprises a device for measuring entropy ΔS and / or enthalpy ΔH as a function of open circuit voltage OCV, and a device for comparing the entropy and / or enthalpy with a reference change value, wherein the reference change value is the average entropy and / or average enthalpy of an electrochemical cell without an internal short circuit ISC.

11. The detection system of claim 8, further comprising means for sending internal short circuit (ISC) detection data to a remote processing system.

12. The detection system according to claim 11, wherein: The remote processing system also triggers ISC warnings and alarms.

13. The detection system according to claim 11, wherein: The teleprocessing system also isolates the cell having the ISC from the rest of the battery cells.

14. The detection system according to claim 8 further comprises a device for causing the electrochemical cell to reach a specific open circuit voltage OCV corresponding to a significant difference in thermodynamic data and / or kinetic data, and a device for measuring a relaxation curve of the open circuit voltage OCV as a function of temperature (T) with respect to the specific OCV.

15. The detection system according to claim 8, further comprising means for measuring entropy data and / or enthalpy data as a function of the state of charge or state of discharge (SOC / SOD) and open circuit voltage (OCV).

16. A charging system for charging a rechargeable battery using terminals connected to internal electrochemical cells, the charging system comprising: a power source connected to the rechargeable battery and arranged to apply a time-varying charging voltage to the battery terminals, thereby generating a charging current that causes the electrochemical cell to be charged, a charging control processor, the charging control processor being used to control the power supply, The charging system further comprises a detection system according to claim 8.

17. A battery cell, comprising the detection system for detecting an internal short circuit (ISC) according to claim 8.

18. The battery cell according to claim 17, wherein: The ISC detection system is embedded in a smart chip, which includes means for sending detection data to a remote system.

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